cappunish20220107.csv

deathrowsize.csv

executions19762021.csv

deathrowrace.csv

Description

Data about the death penalty in the United States as of January 7, 2022, from the non-profit organization Death Penalty Information Center.

Variables—Capital Punishment Dataset

Rows: 51
Columns: 17
$ state     <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "C…
$ region    <chr> "South", "West", "West", "South", "West", "West", "Northeast…
$ division  <chr> "East Southern Central", "Pacific", "Mountain", "West Southe…
$ court     <chr> "Eleventh", "Ninth", "Ninth", "Eighth", "Ninth", "Tenth", "S…
$ dp1       <chr> "yes", "no", "yes", "yes", "yes", "no", "no", "no", "no", "y…
$ dp2       <chr> "yes", "no", "yes", "yes", "yes, in moratorium", "no", "no",…
$ abolished <dbl> NA, 1957, NA, NA, NA, 2020, 2015, 2016, 1981, NA, NA, 1957, …
$ post1976  <dbl> 68, 0, 37, 31, 13, 1, 1, 16, 0, 99, 76, 0, 3, 12, 20, 0, 0, …
$ pre1976   <dbl> 708, 12, 104, 478, 725, 101, 126, 24, 118, 347, 950, 49, 26,…
$ prisoners <dbl> 171, NA, 118, 31, 699, NA, NA, NA, NA, 338, 45, NA, 8, NA, 8…
$ women     <dbl> 5, NA, 3, 0, 22, NA, NA, NA, NA, 3, 1, NA, 1, NA, 0, NA, 0, …
$ freed     <dbl> 7, 0, 10, 1, 5, 0, 0, 1, 0, 30, 7, 0, 1, 21, 2, 0, 0, 1, 11,…
$ clemency  <dbl> 1, 0, 0, 2, 0, 3, 0, 1, 3, 6, 9, 0, 1, 188, 3, 0, 0, 4, 2, 0…
$ life      <chr> "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes"…
$ lifejuvie <chr> "yes", "no", "yes", "no", "no", "yes", "no", "no", "no", "ye…
$ felony    <chr> "no", NA, "yes", "yes", "yes", NA, NA, NA, NA, "yes", "no", …
$ sentence  <chr> "jury + judge", NA, "jury", "jury", "jury", NA, NA, NA, NA, …
# A tibble: 6 × 17
  state  region division  court dp1   dp2   abolished post1976 pre1976 prisoners
  <chr>  <chr>  <chr>     <chr> <chr> <chr>     <dbl>    <dbl>   <dbl>     <dbl>
1 Alaba… South  East Sou… Elev… yes   yes          NA       68     708       171
2 Alaska West   Pacific   Ninth no    no         1957        0      12        NA
3 Arizo… West   Mountain  Ninth yes   yes          NA       37     104       118
4 Arkan… South  West Sou… Eigh… yes   yes          NA       31     478        31
5 Calif… West   Pacific   Ninth yes   yes,…        NA       13     725       699
6 Color… West   Mountain  Tenth no    no         2020        1     101        NA
# … with 7 more variables: women <dbl>, freed <dbl>, clemency <dbl>,
#   life <chr>, lifejuvie <chr>, felony <chr>, sentence <chr>

Variables—Size of Death Row Dataset

Rows: 53
Columns: 2
$ year  <dbl> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978…
$ total <dbl> 517, 575, 631, 642, 334, 134, 244, 488, 420, 423, 482, 539, 691,…
# A tibble: 6 × 2
   year total
  <dbl> <dbl>
1  1968   517
2  1969   575
3  1970   631
4  1971   642
5  1972   334
6  1973   134

Variables—Executions Since 1976 Dataset

Rows: 52
Columns: 46
$ state <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Color…
$ y2021 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2020 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2019 <dbl> 3, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2018 <dbl> 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2017 <dbl> 3, 0, 0, 4, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2016 <dbl> 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2015 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2014 <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 0, 8, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2013 <dbl> 1, 0, 2, 0, 0, 0, 0, 0, 0, 7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2012 <dbl> 0, 0, 6, 0, 0, 0, 0, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2011 <dbl> 6, 0, 4, 0, 0, 0, 0, 1, 0, 2, 4, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2010 <dbl> 5, 0, 1, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y2009 <dbl> 6, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y2008 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0…
$ y2007 <dbl> 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2006 <dbl> 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y2005 <dbl> 4, 0, 0, 1, 2, 0, 1, 1, 0, 1, 3, 0, 0, 0, 5, 0, 0, 0, 0, 0, 1, 0…
$ y2004 <dbl> 2, 0, 0, 1, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0…
$ y2003 <dbl> 3, 0, 0, 1, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2002 <dbl> 2, 0, 0, 0, 1, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y2001 <dbl> 0, 0, 0, 1, 1, 0, 0, 2, 0, 1, 4, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2000 <dbl> 4, 0, 3, 2, 1, 0, 0, 1, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1999 <dbl> 2, 0, 7, 4, 2, 0, 0, 2, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0…
$ y1998 <dbl> 1, 0, 4, 1, 1, 0, 0, 0, 0, 4, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0…
$ y1997 <dbl> 3, 0, 2, 4, 0, 1, 0, 0, 0, 1, 0, 0, 0, 2, 1, 0, 0, 1, 1, 0, 1, 0…
$ y1996 <dbl> 1, 0, 2, 1, 2, 0, 0, 3, 0, 2, 2, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0…
$ y1995 <dbl> 2, 0, 1, 2, 0, 0, 0, 1, 0, 3, 2, 0, 0, 5, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1994 <dbl> 0, 0, 0, 5, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0…
$ y1993 <dbl> 0, 0, 2, 0, 1, 0, 0, 2, 0, 3, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1992 <dbl> 2, 0, 1, 2, 1, 0, 0, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1991 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1990 <dbl> 1, 0, 0, 2, 0, 0, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1989 <dbl> 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1988 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0…
$ y1987 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 5, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0…
$ y1986 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1985 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0…
$ y1984 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 2, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0…
$ y1983 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1982 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1981 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y1979 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1977 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1976 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ ...46 <dbl> 68, 0, 37, 31, 13, 1, 1, 16, 0, 99, 76, 0, 3, 12, 20, 0, 0, 3, 2…
# A tibble: 6 × 46
  state  y2021 y2020 y2019 y2018 y2017 y2016 y2015 y2014 y2013 y2012 y2011 y2010
  <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Alaba…     1     1     3     2     3     2     0     0     1     0     6     5
2 Alaska     0     0     0     0     0     0     0     0     0     0     0     0
3 Arizo…     0     0     0     0     0     0     0     1     2     6     4     1
4 Arkan…     0     0     0     0     4     0     0     0     0     0     0     0
5 Calif…     0     0     0     0     0     0     0     0     0     0     0     0
6 Color…     0     0     0     0     0     0     0     0     0     0     0     0
# … with 33 more variables: y2009 <dbl>, y2008 <dbl>, y2007 <dbl>, y2006 <dbl>,
#   y2005 <dbl>, y2004 <dbl>, y2003 <dbl>, y2002 <dbl>, y2001 <dbl>,
#   y2000 <dbl>, y1999 <dbl>, y1998 <dbl>, y1997 <dbl>, y1996 <dbl>,
#   y1995 <dbl>, y1994 <dbl>, y1993 <dbl>, y1992 <dbl>, y1991 <dbl>,
#   y1990 <dbl>, y1989 <dbl>, y1988 <dbl>, y1987 <dbl>, y1986 <dbl>,
#   y1985 <dbl>, y1984 <dbl>, y1983 <dbl>, y1982 <dbl>, y1981 <dbl>,
#   y1979 <dbl>, y1977 <dbl>, y1976 <dbl>, ...46 <dbl>

Variables—Death Row Demographics Dataset

Rows: 30
Columns: 7
$ state    <chr> "Alabama", "Arizona", "Arkansas", "California", "Florida", "G…
$ black    <dbl> 86, 18, 15, 250, 130, 23, 0, 2, 3, 3, 44, 22, 7, 0, 2, 24, 1,…
$ white    <dbl> 83, 70, 15, 229, 187, 19, 8, 6, 6, 24, 18, 16, 14, 2, 4, 31, …
$ latinx   <dbl> 2, 23, 1, 183, 19, 3, 0, 0, 0, 0, 3, 1, 0, 0, 6, 9, 0, 4, 3, …
$ nativeam <dbl> 0, 4, 0, 9, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 2, 1…
$ asian    <dbl> 0, 3, 0, 28, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 1, 1, 0, …
$ unknown  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1…
# A tibble: 6 × 7
  state      black white latinx nativeam asian unknown
  <chr>      <dbl> <dbl>  <dbl>    <dbl> <dbl>   <dbl>
1 Alabama       86    83      2        0     0       0
2 Arizona       18    70     23        4     3       0
3 Arkansas      15    15      1        0     0       0
4 California   250   229    183        9    28       0
5 Florida      130   187     19        1     1       0
6 Georgia       23    19      3        0     0       0

References

Source: Death Penalty Information Center: State by State

Census Regions and Divisions of the United States

United States Court of Appeals Circuit Map

Legal Information Institute: Furman v. Georgia (1972)